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@ARTICLE{Rudolph:132915,
author = {A. Rudolph$^*$ and M. Song and M. N. Brook and R. L. Milne
and N. Mavaddat and K. Michailidou and M. K. Bolla and Q.
Wang and J. Dennis and A. N. Wilcox and J. L. Hopper and M.
C. Southey and R. Keeman and P. A. Fasching and M. W.
Beckmann and M. Gago-Dominguez and J. E. Castelao and P.
Guénel and T. Truong and S. E. Bojesen and H. Flyger and H.
Brenner$^*$ and V. Arndt$^*$ and H. Brauch$^*$ and T.
Brüning and A. Mannermaa and V.-M. Kosma and D. Lambrechts
and M. Keupers and F. J. Couch and C. Vachon and G. G. Giles
and R. J. MacInnis and J. Figueroa and L. Brinton and K.
Czene and J. S. Brand and M. Gabrielson and K. Humphreys and
A. Cox and S. S. Cross and A. M. Dunning and N. Orr and A.
Swerdlow and P. Hall and P. D. P. Pharoah and M. K. Schmidt
and D. F. Easton and N. Chatterjee and J. Chang-Claude$^*$
and M. García-Closas},
title = {{J}oint associations of a polygenic risk score and
environmental risk factors for breast cancer in the {B}reast
{C}ancer {A}ssociation {C}onsortium.},
journal = {International journal of epidemiology},
volume = {47},
number = {2},
issn = {1464-3685},
address = {Oxford},
publisher = {Oxford Univ. Press},
reportid = {DKFZ-2018-00557},
pages = {526 - 536},
year = {2018},
abstract = {Polygenic risk scores (PRS) for breast cancer can be used
to stratify the population into groups at substantially
different levels of risk. Combining PRS and environmental
risk factors will improve risk prediction; however,
integrating PRS into risk prediction models requires
evaluation of their joint association with known
environmental risk factors.Analyses were based on data from
20 studies; datasets analysed ranged from 3453 to 23 104
invasive breast cancer cases and similar numbers of
controls, depending on the analysed environmental risk
factor. We evaluated joint associations of a 77-single
nucleotide polymorphism (SNP) PRS with reproductive history,
alcohol consumption, menopausal hormone therapy (MHT),
height and body mass index (BMI). We tested the null
hypothesis of multiplicative joint associations for PRS and
each of the environmental factors, and performed global and
tail-based goodness-of-fit tests in logistic regression
models. The outcomes were breast cancer overall and by
estrogen receptor (ER) status.The strongest evidence for a
non-multiplicative joint associations with the 77-SNP PRS
was for alcohol consumption (P-interaction = 0.009),
adult height (P-interaction = 0.025) and current use of
combined MHT (P-interaction = 0.038) in ER-positive
disease. Risk associations for these factors by percentiles
of PRS did not follow a clear dose-response. In addition,
global and tail-based goodness of fit tests showed little
evidence for departures from a multiplicative risk model,
with alcohol consumption showing the strongest evidence for
ER-positive disease (P = 0.013 for global and 0.18 for
tail-based tests).The combined effects of the 77-SNP PRS and
environmental risk factors for breast cancer are generally
well described by a multiplicative model. Larger studies are
required to confirm possible departures from the
multiplicative model for individual risk factors, and assess
models specific for ER-negative disease.},
cin = {C020 / C070 / G110 / L101 / L801},
ddc = {610},
cid = {I:(DE-He78)C020-20160331 / I:(DE-He78)C070-20160331 /
I:(DE-He78)G110-20160331 / I:(DE-He78)L101-20160331 /
I:(DE-He78)L801-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:29315403},
pmc = {pmc:PMC5913605},
doi = {10.1093/ije/dyx242},
url = {https://inrepo02.dkfz.de/record/132915},
}